---
title: "Aves_eje_Cafetero"
author: "Sandra Rairán"
output: 
  flexdashboard::flex_dashboard:
    orientation: row
    social: menu
    source_code: embed
    vertical_layout: fill
---



```{r setup, include=FALSE}
library(flexdashboard)
library(dplyr)
library(tidyr)
library(RColorBrewer)
library(tidyverse)
library(lubridate)

#------------------ Parameters ------------------
# Set colors

# https://www.w3.org/TR/css-color-3/#svg-color
count_color <- "mediumvioletred"
colombia_color <- "seagreen"
color <- "slateblue"
Durationmin_color <- "teal"

#------------------ Data ------------------

data_bird<- read.csv("birds_colombia.csv")

aves_colombia <- 1954
#Cantidad de especies
cant_esp <- length(unique(data_bird$Scientific_Name))

# epecies por año


# distinct values
especies_count <-  group_by(data_bird, year)
especies_count <- summarise(especies_count, unique_especies = n_distinct(Scientific_Name))
especies_count<- especies_count %>% rename(Cantidad_especies = unique_especies) 

#mutate

data_bird <-data_bird %>%  mutate(observation_date = ymd(data_bird$Date))

bird <- data_bird %>% 
  select(Scientific_Name, observation_date, Count) %>% 
  glimpse()


# Observaciones por mes de espcies
df_observaciones <- data_bird %>% 
  mutate(observacion_mes = month(observation_date, label = TRUE),
         observacion_año = year(observation_date)) %>% 
  group_by(Scientific_Name, year, Mes) %>% 
  summarize(observation_count = sum(Count, na.rm = TRUE)) %>% 
  group_by(Scientific_Name, Mes) %>% 
  summarize(observation_count_mean = mean(observation_count) %>% round(1)) %>% 
  ungroup() %>% 
  #complete(Scientific_Name, Mes = meses) %>% 
  replace_na(list(observation_count_mean = 0)) %>% 
  arrange(Scientific_Name, Mes)
  glimpse(df_observaciones)

```

Resumen
=======================================================================


row {data-width=450}
-----------------------------------------------------------------------

### Cantidad de aves en Colombia {.value-box}

```{r}
valueBox(
  value = paste(format(aves_colombia, big.mark = ","), "", sep = " "),
  caption = "Cantidad de aves en Colombia",
  icon = "fas fa-dove",
  color = colombia_color
)
```



### Cantidad especies {.value-box}

```{r}


valueBox(
  value = paste(format(cant_esp, big.mark = ","), " (",
    round(100.2 * cant_esp / aves_colombia, 1),
    "%)",
    sep = ""
  ),
  caption = "Total de Especies Observadas en el Eje Cafetero",
  icon = "fas fa-crow",
  color = count_color
)

```


Column {data-width=650}
-----------------------------------------------------------------------

### Aves observadas segun el tiempo en minutos

```{r}
  plotly::plot_ly(data = data_bird) %>%
  plotly::add_trace(x = ~ data_bird$Duration_Min,
                    y = ~ data_bird$Count,
                    type = "bar", 
                name = "Active",
                marker = list(color = "goldenrod")) %>%
  plotly::layout(barmode = 'stack',
                 yaxis = list(title = "Cantidad de Aves",
                              type = "log"),
                 xaxis = list(title = "Duracion observacion en Minutos"),
                 hovermode = "compare",
                  margin =  list(
                   # l = 60,
                   # r = 40,
                   b = 10,
                   t = 10,
                   pad = 2
                 ))
```

Column {data-width=350}
-----------------------------------------------------------------------


### Aves observadas segun el tiempo en minutos

```{r}
plotly::plot_ly(data = data_bird) %>%
  plotly::add_trace(x = ~ data_bird$Time,
                    type = "histogram", 
                name = "Active",
                marker = list(color = color)) %>%
  plotly::layout(barmode = 'stack',
                 yaxis = list(title = "Hora de inicio pajareada",
                              type = "log"),
                 xaxis = list(title = "Hora de inicio (time)"),
                 hovermode = "compare",
                  margin =  list(
                   # l = 60,
                   # r = 40,
                   b = 10,
                   t = 10,
                   pad = 2
                 ))
     
```

 

### cantidad de especies por año

```{r}

library(reactable)
orange_pal <- function(x) rgb(colorRamp(c("#ffe4cc", "#ff9500"))(x), maxColorValue = 255)


reactable(especies_count, defaultSorted = list(Cantidad_especies = "desc"), columns = list(
  Cantidad_especies = colDef(style = function(value) {
    normalized <- (value - min(especies_count$Cantidad_especies)) / (max(especies_count$Cantidad_especies) - min(especies_count$Cantidad_especies))
    color <- orange_pal(normalized)
    list(background = color)
  })
))
```

Gráficas(Especies por año y meses)
=======================================================================
Column {data-width=400}
------------------------------------------------------------------------------
### Observaciones por fecha
```{r}
     
data_bird %>% 
  count(observation_date) %>% 
  ggplot(aes(x = observation_date, y=n, group = 1)) +
  geom_line( colour = "mediumvioletred", size=1, alpha=0.9, linetype=1) +
   geom_point(color="mediumvioletred", size=2) +
  ggtitle("Observaciones por fecha") +
    labs(x = "Fecha Observacion",
         y = "Observacoines")+
   theme_light()
                         
```

### Observaciones por mes
```{r}
# log10 para Para hacer que los datos con asimetría positiva sean más "normales"

  df_observaciones %>% 
  ggplot(aes(Mes, observation_count_mean)) +
  geom_jitter(color="mediumorchid", size=0.7, alpha=0.5) +
    geom_boxplot(fill = "palegreen", colour = "mediumseagreen") +
    labs(x = "Observaciones por mes",
         y = "Promedio de aves observadas (log10)")+
  theme_light()
```

### Observaciones por mes
```{r}
# log10 para Para hacer que los datos con asimetría positiva sean más "normales"
  
  df_observaciones %>% 
  ggplot(aes(Mes, observation_count_mean)) +
     geom_point(color="purple", alpha=0.8) +
    labs(x = "Observaciones por mes",
         y = "Promedio de aves observadas (log10)")
```

Información
=======================================================================


**Datos** 
Los datos son descargados de la plataforma Ebird sobre mis avistamientos de aves desde el 2018 en el Eje cafetero.